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Dynamic Refugee Matching

Author

Listed:
  • Tommy ANDERSSON
  • Lars EHLERS
  • Alessandro MARTINELLO
Abstract
Asylum seekers are often assigned to localities upon arrival using uninformed matching systems, which lead to inefficient and unfair allocations. This paper proposes an informed dynamic mechanism as an intuitive and easy-to-implement alternative. Our mechanism can be adopted in any dynamic refugee matching problem given locality-specific quotas and that asylum seekers map into specific categories. Any matching selected by the proposed mechanism is Pareto efficient, and envy between localities is bounded by a single asylum seeker. Our simulations show that the proposed mechanism outperforms uninformed mechanisms even in presence of severe misclassification error in the estimation of asylum seeker categories.

Suggested Citation

  • Tommy ANDERSSON & Lars EHLERS & Alessandro MARTINELLO, 2018. "Dynamic Refugee Matching," Cahiers de recherche 22-2018, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    • Handle: RePEc:mtl:montec:22-2018
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    References listed on IDEAS

    as
    1. Bruno Crépon & Esther Duflo & Marc Gurgand & Roland Rathelot & Philippe Zamora, 2013. "Do Labor Market Policies have Displacement Effects? Evidence from a Clustered Randomized Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(2), pages 531-580.
    2. Damiano, Ettore & Lam, Ricky, 2005. "Stability in dynamic matching markets," Games and Economic Behavior, Elsevier, vol. 52(1), pages 34-53, July.
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    6. Tommy ANDERSSON & Lars EHLERS, 2016. "Assigning Refugees to Landlords in Sweden : Stable Maximum Matchings," Cahiers de recherche 13-2016, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    7. Jens Gudmundsson, 2019. "Compromises and Rewards: stable and non-manipulable probabilistic matching," International Journal of Game Theory, Springer;Game Theory Society, vol. 48(2), pages 365-392, June.
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    12. Guillaume Haeringer & Vincent Iehlé, 2019. "Two-Sided Matching with (Almost) One-Sided Preferences," American Economic Journal: Microeconomics, American Economic Association, vol. 11(3), pages 155-190, August.
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    16. Atila Abdulkadiroglu & Tayfun Sönmez, 2003. "School Choice: A Mechanism Design Approach," American Economic Review, American Economic Association, vol. 93(3), pages 729-747, June.
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    19. Andersson, Tommy, 2017. "Refugee Matching as a Market Design Application," Working Papers 2017:16, Lund University, Department of Economics.
    20. Morimitsu Kurino, 2009. "House Allocation with Overlapping Agents: A Dynamic Mechanism Design Approach," Jena Economics Research Papers 2009-075, Friedrich-Schiller-University Jena.
    21. Marek Pycia, 2012. "Stability and Preference Alignment in Matching and Coalition Formation," Econometrica, Econometric Society, vol. 80(1), pages 323-362, January.
    22. Andersson, Tommy & Ehlers, Lars, 2016. "Assigning Refugees to Landlords in Sweden: Efficient Stable Maximum Matchings," Working Papers 2016:18, Lund University, Department of Economics, revised 27 Aug 2018.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. P'eter Bir'o & M'arton Gyetvai, 2021. "Online voluntary mentoring: Optimising the assignment of students and mentors," Papers 2102.06671, arXiv.org.
    2. Mehic, Adrian, 2019. "Immigration and Right-Wing Populism: Evidence from a Natural Experiment," Working Papers 2019:5, Lund University, Department of Economics.
    3. Francesco Campo & Sara Giunti & Mariapia Mendola & Giulia Tura, 2023. "Political Backlash to Refugee Settlement: Cultural and Economic Drivers," Working Papers 522, University of Milano-Bicocca, Department of Economics.
    4. Hagen, Martin, 2022. "Tradable immigration quotas revisited," Journal of Public Economics, Elsevier, vol. 208(C).
    5. Cilali, Buket & Barker, Kash & González, Andrés D. & Salo, Ahti, 2024. "Two-stage stochastic program for environmental resettlement decision-making," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    6. Gina Galindo & Jose Navarro & Jhonattan Reales & Jhoan Castro & Daniel Romero & Sandra Rodriguez A. & Daniel Rivera-Royero, 2022. "Immigrants resettlement in developing countries: A data-driven decision tool applied to the case of Venezuelan immigrants in Colombia," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-16, January.
    7. Biró, Péter & Gyetvai, Márton, 2023. "Online voluntary mentoring: Optimising the assignment of students and mentors," European Journal of Operational Research, Elsevier, vol. 307(1), pages 392-405.

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    More about this item

    Keywords

    forced migration; market design; refugee matching; dynamics; envy; efficiency;
    All these keywords.

    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration

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